The data quality methodology information is organized by
analytical function and provides in-depth knowledge and best practices
for your data quality strategy.
There are a number of key concepts with data quality analysis and
monitoring that include capabilities to:
- Support business-driven rule definition and organization
- Apply rules and reuse consistently across data sources
- Leverage multi-level rule analysis to understand broader data
quality issues
- Evaluate rules against defined benchmarks/thresholds
- Assess and annotate data quality results
- Monitor trends in data quality over time
- Deploy rules across environments
- Run data quality activities on either an impromptu or scheduled
basis using either the user interface or the command line